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Paper Citation Record · LEDGER

Training Noise Token Pruning

As of 15 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2411.18092.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.18092 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:37:55.528782Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

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  • verified fuzzy11
  • unresolved10
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77939b07-84dd-4a7a-935c-e55c0db2f450 · outbound

This paper cites Deep Variational Information Bottleneck.

Training Noise Token Pruning Deep Variational Information Bottleneck

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:37:55.435638Z digest=sha256:db5116fa19e275cb125865872d386ba9b19168ce8d7f16f90fbf3c42aa48be2d

Observation b74d0c2a-0cf7-48c2-9332-db170e35f881 · outbound

This paper cites Computation of channel capacity and rate- distortion functions.

Training Noise Token Pruning Computation of channel capacity and rate- distortion functions

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2a01516a-bdb2-4679-9c36-7cf85d3338ff · outbound

This paper cites Token merging for fast sta- ble diffusion.

Training Noise Token Pruning Token merging for fast sta- ble diffusion

Reference 3

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.446140Z digest=sha256:e6c78507443294c1d357c653755913119cc8ad66e92c2c76e281797c8b51d3e5

Observation a635bddd-4e72-4f24-aa5d-e48390249bc4 · outbound

This paper cites Token Merging: Your ViT But Faster.

Training Noise Token Pruning Token Merging: Your ViT But Faster

Reference 4

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source=pdf_text observed=2026-08-12T11:37:55.450721Z digest=sha256:9334b87ab6b4f163a9552f22583d2e7c30f379e167d36a1f147b209cd9a5da66

Observation ad10926a-036e-4729-b7fc-4ba2eb6944a6 · outbound

This paper cites Elements of information theory.

Training Noise Token Pruning Elements of information theory

Reference 5

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source=pdf_text observed=2026-08-12T11:37:55.455509Z digest=sha256:4fb84672523786d6653fc668e2d1247fe80d3bccfab3b196167d67bcc3392e67

Observation 19c5020e-ad02-4f8f-b02a-b0fb9ef90db5 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Training Noise Token Pruning Imagenet: A large-scale hierarchical image database

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9f40ade0-efb0-4f36-9666-f12052e757dd · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Training Noise Token Pruning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

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source=pdf_text observed=2026-08-12T11:37:55.464268Z digest=sha256:00bc6dc6d47f3b50c2454dc701de8c160d9044fddcce47fe582710ee1d311956

Observation 0146119f-ce3e-4691-98c8-26dbd4c29c24 · outbound

This paper cites Adaptive token sampling for efficient vision transformers.

Training Noise Token Pruning Adaptive token sampling for efficient vision transformers

Reference 8

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.469133Z digest=sha256:850d127f74d73c32bfaa731e7c0fa08dbbaf0d7366a54ec3b24bb56d662578da

Observation 2fcd095d-3a63-41b2-8829-c45a817c7c4c · outbound

This paper cites Power-bert: Accelerating bert inference via progres- sive word-vector elimination.

Training Noise Token Pruning Power-bert: Accelerating bert inference via progres- sive word-vector elimination

Reference 9

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.473343Z digest=sha256:67ff6ff130820d0f222cf819dc85a6d3422cabc6c37360d6f1ce7d0430978957

Observation ca446039-b967-49d5-9f06-be2899078c8c · outbound

This paper cites Which tokens to use? investigating token reduction in vision transformers.

Training Noise Token Pruning Which tokens to use? investigating token reduction in vision transformers

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.477466Z digest=sha256:bf11c2916734f074a79f645b483410eaf18aa0014690b26f22577af7f74200b6

Observation 995f5df0-33a1-4dea-b902-a63c0ef6e474 · outbound

This paper cites Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search.

Training Noise Token Pruning Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search

Reference 11

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source=pdf_text observed=2026-08-12T11:37:55.481635Z digest=sha256:80747a24140b8b89a605533826306c7071367ef36938635c2e7ad9c0f92cf5c4

Observation 35598284-7c5a-49a8-af66-9ce1cca6acfe · outbound

This paper cites Learned token pruning for transformers.

Training Noise Token Pruning Learned token pruning for transformers

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1416ab19-9c89-4010-a2f9-1aea7eb45c8a · outbound

This paper cites Auto-Encoding Variational Bayes.

Training Noise Token Pruning Auto-Encoding Variational Bayes

Reference 13

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source=pdf_text observed=2026-08-12T11:37:55.490385Z digest=sha256:88cefa7e46294d1637156d7ad49292629f8b42fc918bbfe4c567c06cbb08330a

Observation 57d6bcf7-97de-47df-af2e-fe5c3a0cbd10 · outbound

This paper cites Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations.

Training Noise Token Pruning Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations

Reference 14

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source=pdf_text observed=2026-08-12T11:37:55.494689Z digest=sha256:fd03dcccd863818313027f9854b4b950fe3e1dec7ad7497affc12c213721111c

Observation 526a95a1-388a-4b82-a96b-32ad7c0ccbc7 · outbound

This paper cites The pagerank citation ranking: Bringing order to the web.

Training Noise Token Pruning The pagerank citation ranking: Bringing order to the web

Reference 15

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source=pdf_text observed=2026-08-12T11:37:55.499010Z digest=sha256:55ca75fa04252772413043352e3224f74ec30987eb1727be22eaa6579989de31

Observation 45dfab83-8f06-430f-8015-59f9b6a1033e · outbound

This paper cites Dynamicvit: Efficient vision trans- formers with dynamic token sparsification.

Training Noise Token Pruning Dynamicvit: Efficient vision trans- formers with dynamic token sparsification

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.502999Z digest=sha256:184a3a93674997c79223d9f04e7ae65d1be8ed68e97564891a86bfde6a178afe

Observation dd735bfc-7338-4b8a-abe9-9d898480c4e1 · outbound

This paper cites The information bottleneck method.

Training Noise Token Pruning The information bottleneck method

Reference 17

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source=pdf_text observed=2026-08-12T11:37:55.507118Z digest=sha256:39e8f508f3605188505185fe1eff90a316001abe067c6f248152809a39446751

Observation bc6bb1cd-050f-4772-b739-4934a446f0c8 · outbound

This paper cites Training data-efficient image transformers & distillation through atten- tion.

Training Noise Token Pruning Training data-efficient image transformers & distillation through atten- tion

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.512054Z digest=sha256:9f0c7d462aec973d434f3a45aab7e733396b49e51887a8dadcab80dd85b42fba

Observation 1fa4476c-2ed7-4967-8120-0b28381b7ce5 · outbound

This paper cites Attention is all you need.

Training Noise Token Pruning Attention is all you need

Reference 19

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source=pdf_text observed=2026-08-12T11:37:55.516369Z digest=sha256:4e996e36c935ce56caa2a58b503706727601e6cc4f6a32e1edb28e380d17ed0f

Observation 3aa8e526-b52e-44cd-9d03-aa330081a816 · outbound

This paper cites Zero- tprune: Zero-shot token pruning through leveraging of the attention graph in pre-trained transformers.

Training Noise Token Pruning Zero- tprune: Zero-shot token pruning through leveraging of the attention graph in pre-trained transformers

Reference 20

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.520546Z digest=sha256:5b53cb7a3329efd074c86cf6848226fbed65f6ed89a801408f8f000e4e6fb316

Observation 3473bb04-f912-4b64-b405-13aa59e36c60 · outbound

This paper cites Evo-vit: Slow-fast token evolution for dynamic vision transformer.

Training Noise Token Pruning Evo-vit: Slow-fast token evolution for dynamic vision transformer

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.524597Z digest=sha256:19bca2541f02ba5fd398393dff6ee0cc799951e4a461edc14e95d295857fdb66

Observation b110e29c-7bb0-4b0c-8ae1-7303aa730825 · outbound

This paper cites VisionTransformer- WithTNT.

Training Noise Token Pruning VisionTransformer- WithTNT

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T11:37:55.528782Z digest=sha256:4470bf269f6c87ba53f8c2c261e581b95a72d635c1550110754588e7e50b4a94

Pith citing papers

No inbound Pith citation observations are available.